Pérez-Castilla, A, Piepoli, A, Delgado-García, G, Garrido-Blanca, G, and García-Ramos, A. Reliability and concurrent validity of seven commercially available devices for the assessment of movement velocity at different intensities during the bench press. J Strength Cond Res 33(5): 1258–1265, 2019—The aim of this study was to compare the reliability and validity of 7 commercially available devices to measure movement velocity during the bench press exercise. Fourteen men completed 2 testing sessions. One-repetition maximum (1RM) in the bench press exercise was determined in the first session. The second testing session consisted of performing 3 repetitions against 5 loads (45, 55, 65, 75, and 85% of 1RM). The mean velocity was simultaneously measured using an optical motion sensing system (Trio-OptiTrack; “gold-standard”) and 7 commercially available devices: 1 linear velocity transducer (T-Force), 2 linear position transducers (Chronojump and Speed4Lift), 1 camera-based optoelectronic system (Velowin), 1 smartphone application (PowerLift), and 2 inertial measurement units (IMUs) (PUSH band and Beast sensor). The devices were ranked from the most to the least reliable as follows: (a) Speed4Lift (coefficient of variation [CV] = 2.61%); (b) Velowin (CV = 3.99%), PowerLift (3.97%), Trio-OptiTrack (CV = 4.04%), T-Force (CV = 4.35%), and Chronojump (CV = 4.53%); (c) PUSH band (CV = 9.34%); and (d) Beast sensor (CV = 35.0%). A practically perfect association between the Trio-OptiTrack system and the different devices was observed (Pearson's product-moment correlation coefficient (r) range = 0.947–0.995; p < 0.001) with the only exception of the Beast sensor (r = 0.765; p < 0.001). These results suggest that linear velocity/position transducers, camera-based optoelectronic systems, and the smartphone application could be used to obtain accurate velocity measurements for restricted linear movements, whereas the IMUs used in this study were less reliable and valid.

Objective: To compare the accuracy of different devices to predict the bench-press 1-repetition maximum (1RM) from the individual load–velocity relationship modeled through the multiple- and 2-point methods. Methods: Eleven men performed an incremental test on a Smith machine against 5 loads (45–55–65–75–85%1RM), followed by 1RM attempts. The mean velocity was simultaneously measured by 1 linear velocity transducer (T-Force), 2 linear position transducers (Chronojump and Speed4Lift), 1 camera-based optoelectronic system (Velowin), 2 inertial measurement units (PUSH Band and Beast Sensor), and 1 smartphone application (My Lift). The velocity recorded at the 5 loads (45–55–65–75–85%1RM), or only at the 2 most distant loads (45–85%1RM), was considered for the multiple- and 2-point methods, respectively. Results: An acceptable and comparable accuracy in the estimation of the 1RM was observed for the T-Force, Chronojump, Speed4Lift, Velowin, and My Lift when using both the multiple- and 2-point methods (effect size ≤ 0.40; Pearson correlation coefficient [r] ≥ .94; standard error of the estimate [SEE] ≤ 4.46 kg), whereas the accuracy of the PUSH (effect size = 0.70–0.83; r = .93–.94; SEE = 4.45–4.80 kg), and especially the Beast Sensor (effect size = 0.36–0.84; r = .50–.68; SEE = 9.44–11.2 kg), was lower. Conclusions: These results highlight that the accuracy of 1RM prediction methods based on movement velocity is device dependent, with the inertial measurement units providing the least accurate estimate of the 1RM.

Whereas 3D optical motion capture (OMC) systems are considered the gold standard for kinematic assessment in sport science, they present some drawbacks that limit its use in the field. Inertial measurement units (IMUs) incorporating gyroscopes have been considered as a more practical alternative. Thus, the aim of the study was to evaluate the level of agreement for angular velocity between IMU gyroscopes and an OMC system for varying tennis strokes and intensities. In total, 240 signals of angular velocity from different body segments and types of strokes (forehand, backhand and service) were recorded from four players (two competition players and two beginners). The angular velocity of the IMU gyroscopes was compared to the angular velocity from the OMC system. Level of agreement was evaluated by correlation coefficients, magnitudes of errors in absolute and relative values and Bland-Altman plots. Differences between both systems were highly consistent within players’ skill (i.e. along the broad range of velocities) and axes ( x, y, z). Correlations ranged from 0.951 to 0.993, indicating a very strong relationship and concordance. The magnitude of the differences ranged from 4.4 to 35.4 deg·s⁻¹. The difference relative to the maximum angular velocity achieved was less than 5.0%. The study concluded that IMUs and OMC systems showed comparable values. Thus, IMUs seem to be a valid alternative to detect meaningful differences in angular velocity during tennis groundstrokes in field-based experimentation.

Background: caffeine is an ergogenic aid that still needs to be investigated in women’s sports performance. Methods: Eight semi-professional women’s volleyball players (height = 1.63 ± 0.08 m; weight = 66.67 ± 4.74 kg) voluntarily participated in this study. A randomized crossover design was implemented where players underwent caffeine and placebo conditions. In the caffeine condition, participants consumed 5 mg/kg of caffeine based on their body weight before acute training. The evaluations were performed over two weeks of training. In both conditions, the countermovement jump, repeated jumps for 15 s, and handgrip tests were performed. The change of direction was assessed using the 505 test. Well-being was also assessed with a wellness questionnaire. A repeated measures ANOVA and correlation analysis were performed. Results: The repeated measures ANOVA revealed a main effect of supplementation (F (1.7) = 8.41, p = 0.02, η2 = 0.54) across the training week on physical performance. Additionally, there was a positive effect on perceived fatigue (F (1.7) = 7.29, p = 0.03, η2 = 0.51). Conclusions: Caffeine improved performance and fatigue parameters over one week of training. Further research is needed on women, focusing on physical performance and wellbeing, especially during intense periods.

Accuracy and speed are related to performance in tennis. Most research has focused on speed and little is known about the probabilistic structure of error (i.e. accuracy). In the present study 31 advanced players performed a standardised test and accuracy was measured using video analysis. Parameters describing 95% confidence ellipses (CEs) of forehand and backhand were calculated to determine the probabilistic structure of errors. Results showed that for both groundstrokes the long axis of the CEs was oriented almost parallel to the sideline. Despite greater ball speed (~107.2 vs. ~97.3 m • s⁻¹; p < 0.001), the forehand showed a smaller longitudinal distance to the target than the backhand (~123.3 vs. ~164.0 cm; p = 0.024) and a smaller CE area (~34.4 vs. ~40.3 m²; p = 0.045). This means that tennis shot placements fit a bivariate normal distribution (represented by an ellipse), similar to other throwing sports, with differences between the forehand and backhand. Further research will need to explore the underlying causes of these distributions, which in turn may open up opportunities for coaches to modify them in their players according to what is deemed most vital for improved performance.

Physical preparation is becoming more important in amateur tennis player training programs. Yet, when studying stroke performance in these players, there is a lack of evidence on the role of functional power generating capacity. The aim of the study was therefore to determine whether functional power generating capacity correlates with speed and accuracy of forehand and backhand groundstrokes in amateur players. We also studied the correlation with handgrip strength as a more classical measurement of general muscle strength. A total of 21 male amateur players, aged 33.7±4.6 with 17.1±6.7 years of play, were tested. They performed a medicine ball side throw test, a handgrip dynamometer test, and a stroke performance test. Distance of the medicine ball throw on the dominant side positively correlated to the speed of the fastest forehand (r=0.52; P=0.017) and backhand accuracy (r=0.49; P=0.024). There was also a correlation between the handgrip strength on the dominant side and the speed of the fastest forehand (r=0.52, P=0.019). We concluded that groundstroke performance in amateur tennis players depends on functional power generating capacity, but that it is not the principal contributing factor.